(Syllepte) Derogata (Fabricius, 1775) (Lepidoptera: Crambidae) Under Laboratory Conditions

Dannon et al., J. Appl. Biosci. 2021 Efficacy of Beauveria bassiana against the cotton leaf roller, Haritalodes (Syllepte) derogata (Fabricius, 1775) (Lepidoptera: Crambidae) under laboratory conditions.

Journal of Applied Biosciences 157: 16254 - 16266

ISSN 1997-5902

Efficacy of Beauveria bassiana against the cotton leaf roller, Haritalodes (Syllepte) derogata (Fabricius, 1775) (Lepidoptera: Crambidae) under laboratory conditions.

Dannon H. Fabrice1,4,*, Douro Kpindou O. Kobi4, Toffa Mehinto Joelle3, Zantchedji D. M. Désiré1, Zinsou A. Valerien1, Dannon A. Elie2,4, Houndété A. Thomas5, Elégbédé I. A. Maurille T.1, Olou B. Dénis6 1Laboratoire de Phytotechnie, d’Amélioration et de Protection des Plantes (LaPAPP), Faculté d’Agronomie (FA), Université de Parakou, Parakou, Bénin 2Ecole Normale Supérieure (ENS), Université Nationale des Sciences, Technologies, Ingénierie et Mathématiques d’Abomey, Natitingou, Bénin 3Faculté des Sciences et Techniques (FAST), Université Nationale des Sciences, Technologies, Ingénierie et Mathématiques, Dassa-Zoumè, Bénin 4Institut International d’Agriculture Tropicale, 08 BP 0932 Tri Postal, Cotonou, Benin. 5Centre de Recherches Agricoles Coton et Fibres (CRA-CF), Institut National de Recherches Agricoles, Bohicon, Bénin 6Programme Analyse de la Politique Agricole, Centre de Recherches Agricoles, Institut National de Recherches Agricoles, (PAPA/CRA-A/INRAB), Agonkanmey, Bénin *Corresponding author : Dannon Houénoudé Fabrice, Contact : (+229) 95274027, e-mail : [email protected]

Original submitted in on 16th October 2020. Published online at www.m.elewa.org/journals/ on 31st January 2021 https://doi.org/10.35759/JABs.157.10

ABSTRACT Objective: The leaf-roller caterpillar Haritalodes (=Syllepte) derogata (Fabricius, 1775) (Lepidoptera: Crambidae) induces high yield losses by damaging cotton leaves and reducing the photosynthetic activity of the plant. Laboratory bioassays were carried to evaluate the effect of Beauveria bassiana on the survival of H. derogata larvae. Methodology and results: In the first trial, screening of thirteen B. bassiana isolates was performed on third larval instars at 107 conidia.mL-1. In the second trial, effects of five concentrations (105 to 109 conidia.mL-1) of the three best isolates of the fungus were tested. Conidia suspension was applied on each larva topically. Germination rates of conidia used varied between 90.2% to 95.7%, 24 hours after incubation. Five isolates were found to be the most promising namely Bb116, Bb3, Bb11, Bb6 and Bb115. In the second bioassay, caterpillar mortality increased with fungal concentration. Lethal Concentration (LC50) was estimated to 1.18x1015 conidia.mL-1, 1.75x1013 conidia.mL-1, 1.75x1013 conidia.mL-1, 9 days after inoculation for Bb3, Bb11 and Bb115, respectively. Conclusion and application of results: The use of B. bassiana as a biopesticide against H. derogata could be a good alternative method to control the pest. It is an environmentally friendly method with less side effects compared to the application of synthetic pesticides on cotton. This method could be tested in future station and field experiments. Keywords: Cotton, Integrated pest management, Haritalodes (=Syllepte) derogata, Beauveria bassiana, Lethal Concentration.

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INTRODUCTION Cotton crop is the first cash crop of Benin that in the value chain and insect resistance mainly of contributes up to 80% to official export earnings and Lepidopteran species became a major issue to be 13% to GDP (Great Development Product) (Afouda solved for boosting cotton production in Benin. et al., 2013). In 2018-2019 season, the recorded Among these caterpillars of cotton, H. derogata production was 700,000 TM ranking Benin as the (Fabricius, 1775) (Lepidoptera: Crambidae) largest producer in West Africa (Tonavoh, 2019). inducing up to 20-60% of cotton yield loss (Silvie, This increase in cotton production is related to the 1993). Thus, this phyllophagous could alter the expansion of cultivated areas and the use of new photosynthetic activity of the plant. In order to cotton varieties but not to an increase in yield (CRA- economically and ecologically manage cotton insect CF 2018). Yield is heavily limited by pressure from pests, biological control remains an attractive insect pests. In West Africa, insect pests become a option. This control option includes the use of major constraint on increasing cotton production natural enemies of target insect pest species. (Brevault et al., 2017). Indeed, cotton is the one of Several studies reported various natural enemies the most damaged crops with more than 1300 (parasitoids and pathogens) of H. derogata species of insect pests, heavily limiting its (Gahramanova et al., 2020). In this perspective, the productivity (UNCTAD, 2008 cited by Douro entomopathogen Beauveria bassiana (Bals.-Criv.) Kpindou et al., 2013). Among these, phyllophagous Vuill., 1912, is a promising candidate. Different and carpophagous caterpillars are the most isolates were identified infecting a wide range of destructive pests of cotton in Benin. There are two insects (707 species belong to 15 orders) and mites main groups of caterpillar pests according to their (13 species) (Zimmerman 2007; Lambert 2010). feeding preferences (Héma et al., 2009). The first The use of B. bassiana is an environmentally group consisted of defoliators such as the leaf-roller friendly control mean and harmless to human health caterpillar Haritalodes (=Syllepte) derogate F. compared to chemical pesticides (Althouse et al., (Crambidae)), the leaf-eating noctuids Anomis flava 1997; Faria and Wraight, 2001). Fungus kills both F. and Spodoptera littoralis (Boisduval). On the susceptible adult and immature stages (eggs, other hand the second group includes bollworms or larvae) causing the so-called ‘’white muscardine’’ fruit-feeders namely the old world bollworm disease by a simple contact. Pest mortality may Helicoverpa armigera (Hubner), the red bollworm occur with the conidia development process and Diparopsis watersi Rothschild and the spiny dead host becomes a new source of contamination. bollworms Earias insulana (Boisduval) and Earias Four steps are known for the infection of the fungus biplaga (Walker) which feed on fruiting organs namely adhesion, germination and differentiation, (squares, flowers, bolls) (Silvie et al., 2013). penetration, and dissemination within the host and Expansion of cultivated area led to higher to another host (Dannon et al., 2020). It is not consumption of chemical pesticides in order to theoretically possible for insects to develop overcome insect pests damage (Westerberg, 2017). resistance to B. bassiana because the fungus The side effects of chemical insecticide misuses simultaneously uses several modes of action such included the contamination of cotton production as infection by conidia and toxins (Mascarin and area, human hazards (frequent pesticide poisoning, Jaronski, 2016) and as a living organism, it can skin and stomach irritation), insect pest resurgence adapt to various host changes (Sabbahi, 2008). The and resistance, environmental pollution (Lawani et present study was designed to assess the al., 2017; Djihinto et al., 2016; Djihinto et al., 2009). susceptibility of H. derogata to various B. bassiana Cotton is an income generating for all stakeholders isolates under laboratory conditions.

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MATERIALS AND METHODS Insects: Larvae of H. derogata were collected during the International Institute of Tropical Agriculture (IITA), period of 12 to 15 October 2017 on untreated cotton Benin station. They were fed using untreated cotton plants samples at the experimental site of the agricultural leaves. The first generation was used in the different research center, cotton and fiber (CRA-CF), in two bioassays. Only, the third larval instars were tested with regions of central Benin namely Savalou (07°54’.032’’N; B. bassiana isolates. 001°55’.024’’E; 179 m of altitude) and Savè Fungal isolates: Thirteen isolates were used in the first (08°00’.003’’ N; 002°25’.054’’E; 175 m of altitude). They trial and the best three ones were retained for the were reared at (26 ± 1) °C, (70 ± 5) % HR and a second experiment. All isolates were obtained from the photoperiod of 12:12 (L: D) h in the laboratory at collection unit of IITA-Benin (Table 1).

Table 1: Information about B. bassiana isolates used in different trials. Range Abbreviation of fungal Register N° Host Auteur isolates (Country of origin. (Year of isolation) district) 1 Bb2 5644 Eldana sacharina -IITA-Benin (1997) (Benin, Atlantique) 2 Bb3 5645 Eldana sacharina -IITA-Benin (1997) (Benin, Atlantique)) 3 Bb5 5647 Acigona sp. - IITA-Benin (1997)- (Nigeria, Ikom) 4 Bb6 5648 Acigona sp. - IITA-Benin (1997)- (Benin, Alibori) 5 Bb11 5653 Sesamia calamistis -IITA-Benin (1997) (Benin, Atlantique)) 6 Bb115 I93-841 Locusta migratoria -Madagascar (1993) (Madagascar, Toliara) 7 Bb69 I91-623 Zonocerus variegatus -IITA-Benin (1991) (Benin, Atlantique) 8 Bb71 I91-592 Zonocerus variegatus -IITA-Benin (1991) (Benin, Atlantique) 9 Bb84 I91-679 Hieroglyphus -IITA-Benin (1998) (Benin, Alibori) 10 Bb353 - Callosobruchus sp. -IITA-Benin (2001) (Benin, Ouémé) 11 Bb116 I93-842 Locusta migratoria -Madagascar (1993) (Madagascar, vatolalaka) 12 Bb338 2191 ARSEF Pentatomidae Oebalus - Cornell University (Brazil, Fazenda) (USA, 1986) 13 Bb339 3086 ARSEF Leptoglossus fulvicorni -Cornell University (USA, Florida) (USA, 1990)

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Isolates were mass cultured in petri dishes (9 cm Mortality of larvae was checked daily over 15 days. diameter) containing Potato Dextrose Agar (PDA) and Cadavers were dried for 48-72 hours, and transferred in incubated at 26 ± 1°C. When isolates sporulated after petri dishes (9 cm diameter) containing humidified fifteen days, conidia of each isolate were harvested with Whatman filter paper, sealed with parafilm and 0.05% of Tween 80 and filtered. After serial dilution of incubated at 26 °C to check sporulation. The number of initial conidial suspension of each isolate, viability of pupae formed, dead and sporulated larvae and adults conidia was checked on PDA inoculated with 100 µL of emerged were also recorded. the lowest diluted suspension (~104 conidia.mL-1). Assessing of effect of different concentrations of B. Twenty-four (24) hours later, conidia were counted using bassiana on the survival of H. derogata larvae: Three a sub-sample of 100, and viable conidia were estimated isolates (Bb3, Bb11 and Bb115) of B. bassiana were (formula 1) and conidia concentration to be used was used in the current bioassay. Treatments consisted of a calculated accordingly (formula 2) (Douro Kpindou et al., control (Tween 80 à 0.05% without fungus) and five 2012). different concentrations (105, 106, 107, 108, 109 푎 -1 2 3 4 5 6 %푉푖푎푏푙푒 = [ ] x 100 conidia.mL corresponding to 10 , 10 , 10 , 10 , 10 푎+푏 conidia per insect) tested using 3rd larval instars of H. a=number of germinated conidia within 24 hours; b= derogata. number of non-germinated conidia. Data analysis: Mortality rate was estimated based on Co x Vo C′ = the OECD approach (OECD, 2010). Vo + V′ C’ = concentration to be used, Co = concentration of Nd initial conidial suspension; MR = Vo= volume needed and V’= volume to be added. Nu

Bioassays MR= mortality rate, Nd= number of dead larvae, Nu= Screening of B. bassiana isolates: Isolates of B. number of larvae used (normally 20). Sporulation rate bassiana were formulated with Tween 80 (0.05%) at the was assessed basing on the number of larvae dead in concentration 107 conidia. mL-1. Hundred-twenty larvae each treatment. Likewise, the emergence rate was of H. derogata were used for the bioassay. Third instars estimated based on the number of pupae formed by larvae were individually placed in rearing boxes (3.8 cm treatment. Percentages were converted in “Arcsin x 2.9 cm x 4.0 cm) with punched tiny holes for ventilation. (square (p)) transformation” before statistical analysis. There were thirteen isolates used and each of these was Transformed data related to mortality, sporulation and tested on twenty larvae replicated three times in a emergence were subjected to Fisher’s analysis of completely randomized block. Larvae were inoculated by variance (ANOVA) (Steel et al., 1997), using the general the method of Bateman et al. (1996) and Peveling et al. linear model (GLM) procedure of SAS (Version 9.2). The (1997). Each larva received topically 1µL of the fungal post hoc test of Tukey (HSD) at 95% probability was suspension on the pronotum at a concentration of 107 used to separate the means after ANOVA indicated at conidia.mL-1. The rates of germination varied from 90.2% 5%. The lethal concentrations and lethal times were to 95.7%, 24 hours after incubation. Conditions of the estimated using the model of Cox regression (SPSS, laboratory were 26 ± 1°C and 70 ± 5% for averages of 1989- 2007) as described by Douro Kpindou et al. temperature (T) and relative humidity (RH) respectively. (2012).

RESULTS Screening test of isolates: Results from the screening bassiana isolates on third larval instars of H. derogata of B. bassiana isolates revealed the pathogenicity of B. (Fig. 1).

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©Dannon HF, 2020

Fig. 1 Sporulation of B. bassiana on third larval instars of Haritalodes (=Syllepte) derogata.

Significant differences were observed between the Bb11, Bb6, Bb71 and Bb115, respectively. On the other tested isolates when considered larval mortality hand, the sporulation rate of dead larvae was from 3.70 (F=8.1464, P<0.0001) and sporulation rate of dead ± 3.70% (Bb5) to 43.61 ± 3.95% (Bb116) after larvae (F=3.9333, P<0.01) (Fig. 2 and Fig. 3). Indeed, incubation. The highest recorded sporulation rates were after the fifteenth days of inoculating larvae, the 43.60 ± 3.95%, 26.98 ± 6.34%, 25.00 ± 14.43%, 21.54 cumulative mortality varied from 16.67 ± 4.40% (isolate ± 17.20% and 20.55 ± 2.42% for Bb116, Bb3, Bb6, Bb11 Bb69) to 73.33 ± 1.66% (Bb2) compared to the control and Bb115 respectively. However, the sporulation rate (3.33 ± 1.66%). The highest recorded mortality rates was lower on larvae dead following the activity of Bb2 were 73.33 ± 1.66%, 46.66 ± 4.40%, 43.33 ± 7.26%, (9.04 ± 2.14%), Bb5 (3.70 ± 3.70%) and Bb71 (8.33 ± 41.66 ± 3.33%, 41.66 ± 8.81%, 33.33 ± 3.33%, 33.33 ± 8.33%). Moreover, no sporulation was observed for the 6.66% and 31.66 ± 4.44% for Bb2, Bb5, Bb116, Bb3, isolates Bb338, Bb353, Bb69, and Bb84.

Fig. 2 Mean mortality rates induced by 13 B. bassiana isolates at 107 conidia.mL-1 on third larval instars (L3) of H. derogate

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Fig. 3 Mean sporulation rates of 13 B. bassiana isolates at 107 conidia.mL-1 on third larval instars (L3) of H. derogata.

Assessing of effect of different B. bassiana (63.33 ± 4.40%) at the concentration of 109 conidia.mL- concentrations on the survival of H. derogata larvae 1. In isolate Bb11, there was a significant difference Effect of B. bassiana on third larvae stage and adults between the mortality rates (60.00 ± 5.77% and 76.66 ± emergence: The larval mortality rates increased with 1.66%) at 108 and 109 conidia.mL-1, respectively. In the fungal concentrations (Table 2). The mortality induced isolate Bb115 any significant differences were not varied from 31.66 ± 4.40 % to 63.33 ± 4.40 %, 33.33 ± observed between the first 4 concentrations and the 3.33 % to 76.66 ± 1.66 % and 31.66 ± 1.66 % to 58.33 highest mortality was obtained (58.33 ± 4.41%) at the ± 4.41% for the isolates Bb3, Bb11 and Bb115, concentration of 109 conidia.mL-1. When comparing respectively. For the isolate Bb3, there was no difference isolates within each concentration, there was a for larval mortality obtained at the first and the second significant difference within isolates at 109 conidia.mL-1. concentrations, and at the third and fourth The isolate Bb11 induced the highest mortality rate concentrations. The highest mortality rate was recorded (76.66 ± 1.66%) compared to Bb3 and Bb115 at 109 conidia. mL-1.

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Table 2: Effects of B. bassiana on third larval instars of Haritalodes derogata Bb Mortality rate of larvae (%) Concentration Bb3 Bb11 Bb115 ANOVA (Conidia/ml) 105 31.66 ± 4.40 bA 33.33 ± 3.33 bA 31.66 ± 1.66 bA F=0.0904 P=0.9154 106 33.33 ± 3.33 bA 40.00 ± 2.88 bA 35.00 ± 2.88 bA F=1.1331 P=0.4075 107 43.33 ± 9.27 bcA 45.00 ± 5.00 bA 36.66 ± 1.66 bA F=0.5900 P=0.5963 108 53.33 ± 3.33 bcA 60.00 ± 5.77 bcA 41.66 ± 4.40 bA F=6.0523 P=0.06169 109 63.33 ± 4.40 cA 76.66 ± 1.66 cB 58.33 ± 4.41 cA F=14.8527 P=0.01408 Control 8.33 ± 1.66 aA 8.33 ± 4.40 aA 8.33 ± 4.40 aA F=0.3001 P= 0.7540 ANOVA F=15.5130 F=18.6442 F=32.2840 P=0.0001961 P=8.824e-05 P=7.355e-06 *There is no significant difference between means followed by the same lowercase letters shown in the same column (ANOVA followed by Tukey test at 5%). *There is no significant difference between means followed by the same capital letters shown in the same line (ANOVA followed by Tukey test at 5%).

The emergence rate of H. derogata adults decreased concentrations in each isolate (P˂0.05). Nevertheless, with the increase in fungal concentrations (Table 3). when comparing isolates for each concentration, no Adult emergence was significantly affected by significant differences occurred.

Table 3: Effects of B. bassiana on emergence of Haritalodes derogata Bb Emergence rate of moths (%) Concentration Bb3 Bb11 Bb115 ANOVA (Conidia/ml) 5 10 79.84 ± 7.56 abA 75.39 ± 5.72 abA 80.58 ± 4.58 abA F=0.3723 P=0.7107 6 10 70.63 ± 7.57 aA 88.38 ± 5.82 bA 79.80 ± 4.19 aA F=4.8867 P=0.08434 7 10 85.55 ± 8.67abA 61.28 ± 4.70 abA 76.06±5.19 aA F=2.3823 P=0.2083 8 10 68.33 ± 4.40 aA 55.55 ± 5.55 abA 73.97 ± 2.06 aA F=4.7484 P=0.08783 9 10 71.95 ± 3.21 aA 33.33 ± 17.63 aA 63.21 ± 3.72 aA F=3.0347 P=0.1578 Control 96.29 ± 3.70 bA 92.96 ± 3.53 bA 96.29 ± 3.70 bA F=0.2310 P= 0.8043 ANOVA F=4.9185 P=0.01568 F=4.899 P=0.01129 F=6.9204 P=0.004876 *There is no significant difference between means followed by the same lowercase letters shown in the same column (ANOVA followed by Tukey test at 5%). *There is no significant difference between means followed by the same capital letters shown in the same line (ANOVA followed by Tukey test at 5%).

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Lethal concentration (LC50) of B. bassiana on third model provided a good estimation of the different larvae stage: Analysis of Cox regression indicated that parameters. Values of B showed the existence of a dose- the different fungal concentrations used were significant response relationship. This relationship was strong for and affected larval survival (P < 0.05) (Table 4). The the Bb11 isolate giving the highest B value (B = 0.087).

Table 4: Estimation of B values and Wald coefficients with Cox regression model for B. bassiana and third instars larvae of H. derogata B. bassiana H. derogata B SE Wald df Sig. isolate stage Bb3 L3 0.069 0.019 13.755 1 0.000 Bb11 L3 0.087 0.019 20.589 1 0.000 Bb115 L3 0.055 0.018 8.932 1 0.003 B: B value of the Cox regression; SE: standard error; Wald: Wald coefficient; df: degree of freedom; Sig: probability.

The LC50 curves for isolates are depicted in figures (5, and 2.19 x 1020 conidia per insect were needed to kill 6 and 7). For all isolates, the dose-response effect was 50% of 3rd larval instars, in 5, 7 and 9 days (Fig. 6) on significant and depends on the B value. Higher is B the other hand. The isolate Bb11 gave the highest B value, the narrower are the confidence intervals. It had value (0.087) and therefore the lowest LC50 values. The to 3.52 x 1026, 5.17 x 1020 and 1.18 x 1015 conidia.mL-1 width of the confidence intervals was narrower for Bb11 of isolate Bb3, i.e. 3.52 x 1023, 5.17 x 1017 and 1.18 x 1012 compared to those of the other isolates. Thus, 1.73 x conidia by insects to kill 50% of the 3rd larval instars, in 1019, 4.91 x 1015 and 1.75 x 1013 conidia.mL-1 of Bb11 i.e. 5, 7 and 9 days respectively (Fig. 5) on the one hand. 1.73 x 1016, 4.91 x 1012 and 1.75 x 1010 conidia per insect Likewise, 8.78 x 1035, 4.08 x 1029 and 2.19 x 1023 were needed to kill 50% 3rd larval instars of H. derogata conidia.mL-1 of Bb115 isolate i.e. 8.78 x 1032, 4.08 x 1026 in 5, 7 and 9 days respectively (Fig. 7).

250

200 LC50 Up CI 150 Low CI

100

50 Log(LC50) (conidia/ml) Log(LC50)

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Days after inoculation Fig. 5 LC50 values after treatment of the third stage of Haritalodes (=Syllepte) derogata to various doses of Bb3.

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250

200 LC50 Up CI 150 Low CI

100

Log(LC50)(conidia/ml) 50

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Days after inoculation

Fig. 6 LC50 values after treatment of the third stage of Haritalodes (=Syllepte) derogata to various doses of Bb115.

250

200 LC50 Up CI 150 Low CI

100

50 Log(LC50) (conidia/ml) Log(LC50)

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Days after inoculation

Fig. 7 LC50 values after treatment of the third stage of Haritalodes (=Syllepte) derogata to various doses of Bb11.

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DISCUSSION Mortality and sporulation of larvae: Results of this isolates are found to be promising due to their ability to study indicated that the third larval stages were cause a high rate of mortality and to induce a relatively susceptible to infection of B. bassiana isolates tested. high sporulation rate. These included the isolates Bb116, Mortality rate is depending on the type of isolate. Indeed, Bb3, Bb11, Bb6 and Bb115. the highest mortality rate was obtained with the isolate Effect of concentrations on larvae and adults’ Bb2. Such difference could be explained by its great emergence: The most promising isolates Bb3, Bb11 capacity to produce enzymes and more toxic metabolites and Bb115 used for assessing the effect of different than others (Ferron, 1981). Valda et al. (2003) obtained concentrations were chosen taking into account their similar results with mortality that ranging between 70 and origin from Benin (case of Bb3 and Bb11) and their 96 % in Plutella xylostella treated with different B. effectiveness on other Lepidopteran pests such as H. bassiana isolates. In addition to Bb2, other isolates armigera (Douro Kpindou et al., 2012) and M. vitrata namely Bb116, Bb11, Bb3 and Bb5 induced statistically (Toffa Mehinto, 2014) for the cases of Bb11 and Bb115, similar mortality rates and higher virulence on the tested respectively. The mortality rates increased with the insect host. The difference in virulence between the concentration within each isolate. This suggests that the various isolates may be related to their origin f and in mortality rate depends on the quantity of conidia some cases to the first species from which the isolate received. In some isolates, several concentrations was cultured (same insect family or order). Our findings induced similar mortality rate. For example, in isolate were in concordance with previous studies done by Bb11, no significant difference was obtained for McCoy et al. (1988) and Goettel, (1992), who stated that concentrations 105, 106 and 107 conidia per mL, and the an isolate was generally more virulent to the family and highest mortality was recorded at 108 and 109 conidia per host area from which it has been isolated. Likewise, mL using the third larval instars of H. derogata. The sporulation rate varied from isolate to isolate and the highest mortality rate was observed in Bb11 (76.66 ± highest on dead larvae resulted from the use of Bb116. 1.66%) with the lowest emergence rate (33.33 ± In this perspective, some isolates induced a germination 17.63%) of adults suggests that Bb11 was better of the fungus on the cuticle of incubated cadavers. This compared to the other isolates Bb 3 and Bb115. variability, which due to their difference of pathogenicity Lethal Concentration (LC50) of B. bassiana on third results from their virulence on the larvae of H. derogata. H. derogata larval stage: Models that combine time and Similar results have been reported by Douro Kpindou et dose effects seem to be more appropriate for assessing al. (2012) and Toffa-Mehinto (2014) on Helicoverpa the effectiveness of a pathogen or pesticide on target armigera (Hübner) (Lepidoptera: Noctuidae) and Maruca insect species (Robertson et al., 1992). Of these Cox vitrata Fabricius (Lepidoptera; Crambidae), respectively. regression model was more flexible in the analysis of In addition, dead larvae from some isolates such as bioassays on biopesticides than other models such as Bb338, Bb353, Bb69 and Bb84 did not sporulate. Probit and Logit analyses (Douro Kpindou et al., 2012). Moreover, other isolates namely Bb2, Bb5 and Bb71 had Probit analysis and Logit regression analysis have found a low sporulation rate less than 10% but a higher wide use in modelling the probability of a dose response mortality as mentioned previously. The susceptibility of (Finney, 1971; Robertson et al., 1992). Cox regression the insect would therefore be influenced by their innate models based on the time-dose relationship of B. virulence. This observation was in agreement with the bassiana isolates for the survival of infected larvae of H. views of Soetopo (2004) who reported that the innate derogata fitted well in the current study. All B values virulence of the isolate could induce high mortality with given by Cox regression model were all significant low sporulation rate. However, the choice of isolates (P˂0.05). In consequent, our data showed a significant depends primarily on their pathogenicity and the effect / dose response. Similarly, the LC50 curves had susceptibility of the host insect (Prior, 1990; Tanada and good trend and their confidence intervals were relatively Kaya, 1993;). In the present case, when identifying the narrower. Our results were comparable to those most virulent isolates after screening, sporulation and obtained by Douro Kpindou et al. (2012) when using mortality could be determining parameters in the choice virulent isolates of fungi M. anisopliae and B. bassiana of the most virulent isolates as suggested by Jamal on H. armigera. Based on LC50, isolate Bb11 was found (2008) and Groden & Lockwood (1991). Thus, five to be more virulent followed by Bb3 and Bb115.

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CONCLUSION AND APPLICATION OF RESULTS Among B. bassiana isolates used for the screening, Three of virulent isolates were more promising (Bb11, some showed their potential for the control of H. Bb3 and Bb115) and could be included in a new strategy derogata through their virulence. These isolates delayed of cotton integrated pest management. the growth of treated caterpillars and finally killed them.

ACKNOWLEDGMENTS We thank the national fund for scientific research and control of cotton pests (LuBiRaC) in Benin]. We thank technological innovation from Benin (FNRSIT) for Robert AHOMAGNON for his technical assistance at the financial support of this study. We also thank the other International Institute of Tropical Agriculture (IITA- members of the project "Lutte biologique contre les Benin). ravageurs du cotonnier (LuBiRaC) au Bénin" [Biological

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